Advertisement

Joint Learning for Attribute-Consistent Person Re-Identification

  • Sameh KhamisEmail author
  • Cheng-Hao Kuo
  • Vivek K. Singh
  • Vinay D. Shet
  • Larry S. Davis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8927)

Abstract

Person re-identification has recently attracted a lot of attention in the computer vision community. This is in part due to the challenging nature of matching people across cameras with different viewpoints and lighting conditions, as well as across human pose variations. The literature has since devised several approaches to tackle these challenges, but the vast majority of the work has been concerned with appearance-based methods. We propose an approach that goes beyond appearance by integrating a semantic aspect into the model. We jointly learn a discriminative projection to a joint appearance-attribute subspace, effectively leveraging the interaction between attributes and appearance for matching. Our experimental results support our model and demonstrate the performance gain yielded by coupling both tasks. Our results outperform several state-of-the-art methods on VIPeR, a standard re-identification dataset. Finally, we report similar results on a new large-scale dataset we collected and labeled for our task.

Keywords

Joint Model Correct Match Pairwise Constraint Semantic Aspect Hinge Loss 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    An, L., Kafai, M., Yang, S., Bhanu, B.: Reference-based person re-identification. In: AVSS (2013)Google Scholar
  2. 2.
    Bak, S., Corvee, E., Bremond, F., Thonnat, M.: Person re-identification using spatial covariance regions of human body parts. In: AVSS (2010)Google Scholar
  3. 3.
    Berlin, B., Kay, P.: Basic color terms: Their universality and evolution. University of California, Berkeley (1969)Google Scholar
  4. 4.
    Bourdev, L.D., Maji, S., Malik, J.: Describing people: A poselet-based approach to attribute classification. In: ICCV (2011)Google Scholar
  5. 5.
    Chen, H., Gallagher, A., Girod, B.: Describing clothing by semantic attributes. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part III. LNCS, vol. 7574, pp. 609–623. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  6. 6.
    Cheng, D.S., Cristani, M., Stoppa, M., Bazzani, L., Murino, V.: Custom pictorial structures for re-identification. In: BMVC (2011)Google Scholar
  7. 7.
    Farenzena, M., Bazzani, L., Perina1, A., Murino, V., Cristani, M.: Person re-identification by symmetry-driven accumulation of local features. In: CVPR (2010)Google Scholar
  8. 8.
    Gheissari, N., Sebastian, T.B., Tu, P.H., Rittscher, J.: Person reidentification using spatiotemporal appearance. In: CVPR (2006)Google Scholar
  9. 9.
    Gray, D., Brennan, S., Tao, H.: Evaluating appearance models for recognition, reacquisition, and tracking. In: PETS (2007)Google Scholar
  10. 10.
    Gray, D., Tao, H.: Viewpoint invariant pedestrian recognition with an ensemble of localized features. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part I. LNCS, vol. 5302, pp. 262–275. Springer, Heidelberg (2008) CrossRefGoogle Scholar
  11. 11.
    Hirzer, M., Roth, P.M., Köstinger, M., Bischof, H.: Relaxed pairwise learned metric for person re-identification. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part VI. LNCS, vol. 7577, pp. 780–793. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  12. 12.
    Köstinger, M., Hirzer, M., Wohlhart, P., Roth, P.M., Bischof, H.: Large scale metric learning from equivalence constraints. In: CVPR (2012)Google Scholar
  13. 13.
    Kuo, C.H., Khamis, S., Shet, V.: Person re-identification using semantic color names and rankboost. In: WACV (2013)Google Scholar
  14. 14.
    Lampert, C.H., Nickisch, H., Harmeling, S.: Learning to detect unseen object classes by between-class attribute transfer. In: CVPR (2009)Google Scholar
  15. 15.
    Layne, R., Hospedales, T.M., Gong, S.: Person re-identification by attributes. In: BMVC (2012)Google Scholar
  16. 16.
    Layne, R., Hospedales, T.M., Gong, S.: Towards person identification and re-identification with attributes. In: Fusiello, A., Murino, V., Cucchiara, R. (eds.) ECCV 2012 Ws/Demos, Part I. LNCS, vol. 7583, pp. 402–412. Springer, Heidelberg (2012) Google Scholar
  17. 17.
    Liu, C., Gong, S., Loy, C.C., Lin, X.: Person re-identification: What features are important? In: Fusiello, A., Murino, V., Cucchiara, R. (eds.) ECCV 2012 Ws/Demos, Part I. LNCS, vol. 7583, pp. 391–401. Springer, Heidelberg (2012) Google Scholar
  18. 18.
    Ma, B., Su, Y., Jurie, F.: Local descriptors encoded by fisher vectors for person re-identification. In: Fusiello, A., Murino, V., Cucchiara, R. (eds.) ECCV 2012 Ws/Demos, Part I. LNCS, vol. 7583, pp. 413–422. Springer, Heidelberg (2012) Google Scholar
  19. 19.
    Mignon, A., Jurie, F.: Pcca: A new approach for distance learning from sparse pairwise constraints. In: CVPR (2012)Google Scholar
  20. 20.
    Pedagadi, S., Orwell, J., Velastin, S., Boghossian, B.: Local fisher discriminant analysis for pedestrian re-identification. In: CVPR (2013)Google Scholar
  21. 21.
    Prosser, B., Gong, S., Xiang, T.: Multi-camera matching using bi-directional cumulative brightness transfer functions. In: BMVC (2008)Google Scholar
  22. 22.
    Prosser, B., Zheng, W.S., Gong, S., Xiang, T.: Person re-identification by support vector ranking. In: BMVC (2010)Google Scholar
  23. 23.
    Shalev-Shwartz, S., Singer, Y., Srebro, N., Cotter, A.: Pegasos: Primal estimated sub-gradient solver for SVM. Mathematical Programming, Series B 127(1), 3–30 (2011)CrossRefzbMATHMathSciNetGoogle Scholar
  24. 24.
    Sharmanska, V., Quadrianto, N., Lampert, C.H.: Learning to rank using privileged information. In: ICCV (2013)Google Scholar
  25. 25.
    Torresani, L., Lee, K.: Large margin component analysis. In: NIPS (2007)Google Scholar
  26. 26.
    Vapnik, V., Vashist, A.: A new learning paradigm: Learning using privileged information. In: IJCNN (2009)Google Scholar
  27. 27.
    Vaquero, D.A., Feris, R.S., Tran, D., Brown, L.M.G., Hampapur, A., Turk, M.: Attribute-based people search in surveillance environments. In: WACV (2009)Google Scholar
  28. 28.
    Weinberger, K.Q., Saul, L.K.: Distance metric learning for large margin nearest neighbor classification. JMLR (2009)Google Scholar
  29. 29.
    Wu, Y., Mukunoki, M., Funatomi, T., Minoh, M., Lao, S.: Optimizing mean reciprocal rank for person re-identification. In: AVSS (2011)Google Scholar
  30. 30.
    Zhao, R., Ouyang, W., Wang, X.: Unsupervised salience learning for person re-identification. In: CVPR (2013)Google Scholar
  31. 31.
    Zheng, W.S., Gong, S., Xiang, T.: Person re-identification by probabilistic relative distance comparison. In: CVPR (2011)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Sameh Khamis
    • 1
    Email author
  • Cheng-Hao Kuo
    • 2
  • Vivek K. Singh
    • 3
  • Vinay D. Shet
    • 4
  • Larry S. Davis
    • 1
  1. 1.University of MarylandCollege ParkUSA
  2. 2.Amazon.comSeattleUSA
  3. 3.Siemens Corporate ResearchPrincetonUSA
  4. 4.GoogleMountain ViewUSA

Personalised recommendations